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The Program for AI and Research in Cardiovascular Medicine (PARC) leverages artificial intelligence to improve the interpretation of cardiovascular diagnostic data. Our innovative research has the power to facilitate precision medicine and improve patient outcomes.

About our Research

At The University of Kansas Medical Center, we are developing a collaborative research program reevaluating electrocardiograms (ECG) both in patients without established heart disease and those with cardiac abnormalities, like conduction diseases, arrhythmias and cardiac resynchronization therapy (CRT) for heart failure.

We are investing in a large database linking clinical ECGs to clinical outcomes that we hope to leverage for training predictive AI algorithms. We hope to pursue research in novel analytic methods and machine-learning techniques to improve diagnostic and predictive utility. Eventually, our goal is to bring the fruits of such research for implementation in clinical practice to improve diagnostics, patient risk stratification and target appropriate therapeutics.

Learn more about our approach and innovative methods

Amit Noheria giving an update on AI research in the CVM Department
Jake Baer presenting his abstract on QRS 3D-voltage-time-interval differences in healthy vs. cardiomyopathy patients
Chris Harvey presenting his abstract on AI model to classify sex from ECG
Ashley DeBauge presenting her abstract on diagnosing LVH on ECG in those with LBBB
Tyan Fairbank presenting her abstract on ECG correlates of RV structural and functional abnormalities in those with RBBB
Sean Lacy presenting his abstract on change in QRS 3D-voltage-time-integral predicting CRT response for pacing induced cardiomyopathy
Carine Tabak being awarded the Kathy Roberts Batenic Summer Fellowship
Sarah Baghdadi being awarded the Kathy Roberts Batenic Summer Fellowship
KU School of Medicine

University of Kansas Medical Center
Cardiovascular Medicine
3901 Rainbow Boulevard
Mailstop 4023
Kansas City, KS 66160